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001-es BibID:	BIBFORM100562
035-os BibID:	(cikkazonosító)577 (WoS)000711370100001 (Scopus)85116031074
Első szerző:	Hoffmann Miklós (matematikus, informatikus)
Cím:	Is It a Cube? Common Visual Perception of Cuboid Drawings / Hoffmann Miklós, Németh László
Dátum:	2021
ISSN:	2227-7102
Megjegyzések:	A cube is one of the most fundamental shapes we can draw and can observe from a drawing. The two visualization methods most commonly applied in mathematics textbooks and education are the axonometric and the perspective representations. However, what we see in the drawing is really a cube or only a general cuboid (i.e., a polyhedron with different edge lengths). In this experimental study, 153 first-year ( 19?20-year-old) students, two-thirds of them being female, were asked to interactively adjust a cuboid figure until they believe what they see is really a cube. We were interested in how coherently people, who are actually students of arts studies and engineering with advanced spatial perception skills in most cases, evaluate these drawings. What we have experienced is that for most people there is a common visual understanding of seeing a cube (and not a general cuboid). Moreover, this common sense is surprisingly close to the conventions applied in axonometric drawings, and to the theoretical, geometric solution in the case of three-point perspective drawings, which is the most realistic visualization method.
Tárgyszavak:	Természettudományok Matematika- és számítástudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk visualization in education visual perception
Megjelenés:	Education Sciences. - 11 : 10 (2021), p. 1-17. -
További szerzők:	Németh László
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM106845
035-os BibID:	(cikkazonosító)101 (WoS)000938554700001 (Scopus)85148767987
Első szerző:	Tóth Róbert (informatikus)
Cím:	Lossless Encoding of Mental Cutting Test Scenarios for Efficient Development of Spatial Skills / Róbert Tóth, Miklós Hoffmann, Marianna Zichar
Dátum:	2023
ISSN:	2227-7102
Megjegyzések:	In the last decade, various mobile applications have been developed to improve and measure spatial abilities using different spatial tests and tasks through augmented reality (AR), Virtual Reality (VR), or embedded 3D viewers. The Mental Cutting Test (MCT) is one of the most well-known and popular tests for this purpose, but it needs a vast number of tasks (scenarios) for effective practice and measurement. We have recently developed a script-aided method that automatically generates and permutes Mental Cutting Test scenarios and exports them to an appropriate file format (to GLB (glTF 2.0) assets) representing the scenarios. However, the significant number of permutations results in more than 1,000,000 assets, requiring more than 6 GB of storage space. This paper introduces an encoding scheme consisting of four stages to handle this issue through significantly reducing the storage space, making the app suitable for everyday individual use, even on a mobile phone. The proposed method encodes a subset of assets from which it can decode the whole dataset with 3% time complexity compared to classical Blender's computations, exceeding the compression ratio of 10,000 and storage space saving 99.99%. This paper explains the features of the original assets, introduces the encoding and decoding functions with the format of documents, and then measures the solution's efficiency based on our dataset of MCT scenarios.
Tárgyszavak:	Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk Mental Cutting Test augmented reality GLB assets encoding compression
Megjelenés:	Education Sciences. - 13 : 2 (2023), p. 1-21. -
További szerzők:	Hoffmann Miklós (1966-) (matematikus, informatikus) Bodroginé Zichar Marianna (1971-) (informatikus, matematikus)
Pályázati támogatás:	ÚNKP-22-3 Egyéb
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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